drm subsystem AI patch review

This topic came up at kernel maintainers summit and some other groups have been playing around with it, particularly the BPF folks, and Chris Mason's work on kernel review prompts[1] for regressions. Red Hat have asked engineers to investigate some workflow enhancements with AI tooling, so I decided to let the vibecoding off the leash.

My main goal:

- Provide AI led patch review for drm patches

- Don't pollute the mailing list with them at least initially.

This led me to wanting to use lei/b4 tools, and public-inbox. If I could push the patches with message-ids and the review reply to a public-inbox I could just publish that and point people at it, and they could consume it using lei into their favorite mbox or browse it on the web.

I got claude to run with this idea, and it produced a project [2] that I've been refining for a couple of days.

I started with trying to use Chris' prompts, but screwed that up a bit due to sandboxing, but then I started iterating on using them and diverged.

The prompts are very directed at regression testing and single patch review, the patches get applied one-by-one to the tree, and the top patch gets the exhaustive regression testing. I realised I probably can't afford this, but it's also not exactly what I want.

I wanted a review of the overall series, but also a deeper per-patch review. I didn't really want to have to apply them to a tree, as drm patches are often difficult to figure out the base tree for them. I did want to give claude access to a drm-next tree so it could try apply patches, and if it worked it might increase the review, but if not it would fallback to just using the tree as a reference.

Some holes claude fell into, claude when run in batch mode has limits on turns it can take (opening patch files and opening kernel files for reference etc), giving it a large context can sometimes not leave it enough space to finish reviews on large patch series. It tried to inline patches into the prompt before I pointed out that would be bad, it tried to use the review instructions and open a lot of drm files, which ran out of turns. In the end I asked it to summarise the review prompts with some drm specific bits, and produce a working prompt. I'm sure there is plenty of tuning left to do with it.

Anyways I'm having my local claude run the poll loop every so often and processing new patches from the list. The results end up in the public-inbox[3], thanks to Benjamin Tissoires for setting up the git to public-inbox webhook.

I'd like for patch submitters to use this for some initial feedback, but it's also something that you should feel free to ignore, but I think if we find regressions in the reviews and they've been ignored, then I'll started suggesting it stronger. I don't expect reviewers to review it unless they want to. It was also suggested that perhaps I could fold in review replies as they happen into another review, and this might have some value, but I haven't written it yet. If on the initial review of a patch there is replies it will parse them, but won't do it later. 

[1]  https://github.com/masoncl/review-prompts

[2] https://gitlab.freedesktop.org/airlied/patch-reviewer

[3] https://lore.gitlab.freedesktop.org/drm-ai-reviews/

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